Inspecting Edge Data Integrity with Aggregated Signature in Distributed Edge Computing Environment
ABSTARCT :
In the edge computing environment, app vendors can cache their data on a large number of geographically distributed edge servers to serve their users. However, those cached data are particularly vulnerable to both intentional and accidental corruption, which makes data security a major concern in the EC environment. Given limited computing resources of edge servers, how to effectively and efficiently inspect those data over tremendous edge servers is a critical and open problem. To tackle this edge data integrity (EDI) problem, we first study the entities, threats, system objectives, and the inspection mechanism, then propose a novel approach named EDI-S for inspecting the integrity of edge data and localizing the corrupted ones. Based on the elliptic curve, EDI-S generates one digital signature as the integrity proof for each replica. Then, multiple integrity proofs are aggregated to be inspected together. This mechanism allows the integrity of tremendous cache data on multiple edge servers can be inspected altogether via an aggregate verification. EDI-S also provides two methods for localizing the corrupted data on edge servers, one for small-scale scenarios and the other for large-scale scenarios. Both theoretical analysis and experimentally evaluation demonstrate that EDI-S can solve the EDI problem effectively and efficiently.
EXISTING SYSTEM :
? Smart grid (SG) is no longer fiction, as a number of utility companies have replaced or implemented smart grid alongside existing power grid.
? We can leverage the inherent capabilities of efficient communication, computation and storage provided by the fog computing paradigm as suggested by existing fogenabled schemes for secure data aggregation.
? Existing fog-enabled data aggregation schemes in SG, such as those presented in , have a number of limitations.
? While, in traditional aggregation schemes, there exist an entity named ‘aggregator’ which is supposed to perform aggregation and provide the storage capability.
DISADVANTAGE :
? This new and critical problem is referred to as the edge data integrity (EDI) problem in this paper.
? It is a challenging problem as the edge data replicas are cached on geographically-distributed edge servers rather than app vendors’ own servers managed in-house.
? A possible solution to the EDI problem is to apply one of the existing CDI approaches. However, the EDI problem is fundamentally different from the CDI problem.
? We make the first attempt to study the EDI problem from the app vendor’s perspective, including the entities, threats, system objectives, and inspection mechanism involved.
PROPOSED SYSTEM :
• In this paper, a new fog-enabled privacy-preserving data aggregation scheme (FESDA) is proposed.
• The scheme proposed in is faulttolerant with lower computational cost, however, it requires an additional round of communication among the participants of the protocol (fog-node, trusted authority and the cloud); thus, further increasing the communication cost.
• We demonstrate the effectiveness of the proposed scheme with performance and security analysis.
• We propose an efficient fog-enabled privacy preservation data aggregation scheme in the SG IoT network.
• In our proposed model FN is responsible for the aggregation of users’ consumption data and forwarding it to CC.
ADVANTAGE :
? To compare their performance against EDI-S, we follow the idea of Sequential Localization of EDI-S to localize corrupted data by inspecting each edge data replicas individually and sequentially.
? Leveraging the unique features offered by aggregate signature mechanism, EDI-S can inspect the integrity of massive edge data replicas efficiently.
? We propose EDI-S, a novel EDI approach for inspecting the integrity of edge data replicas and localizing corrupted ones with high efficiency.
? The efficiency of an approach is evaluated by its computational overhead, measured by the computation time taken, the lower the better.
? An approach is urgently needed for effectively and efficiently inspecting the integrity of app vendors’ data cached on edge servers.
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